Abstract 929: The molecular landscape of premenopausal versus postmenopausal breast cancer in patients without inherited predisposition mutations
Authors: Ahmad Charifa, Andre Goy, Andrew Pecora, Deena Graham, Donna McNamara, Andrew Ip, Wanlong Ma, Maher Albitar
Journal: Cancer Research (2023)

Abstract Breast cancer in premenopausal women (preM) is frequently associated with worse prognosis compared to that in postmenopausal women (postM). There is, however, a paucity of studies characterizing molecular alterations in premenopausal patients compared to postmenopausal ones in patients with breast cancer, but without any evidence of predisposition inherited mutations. We used molecular profiling of DNA and RNA using next generation sequencing (NGS) and evaluated the molecular differences between PreM and post-M breast cancers in patient without risk of predisposition to cancer. Case descriptions were collected by COTA, inc. This included 52 patients with breast cancer evaluated clinically at a referral cancer center (John Theurer Cancer Center, Hackensack, NJ, USA) and the DNA and RNA of their tissue samples were evaluated by Genomic Testing Cooperative using next generation sequencing (NGS) of a targeted panel of 1,408 RNA genes and 434 DNA genes. All patients were treated with standard of care therapy by subspecialized oncologists. Machine learning algorithm and Geometric Mean Naïve Bayesian (GMNB) were used to select RNA genes and distinguish between preM and postM cases. PreM patients showed lower cumulative survival proportion (P=0.03). TP53, PIK3CA and GATA3 mutations were the most common mutations in preM and postM patients. However, PTEN mutation was more common in preM cases. The machine learning system chose the expression level of 20 RNA genes (p=0.001) that distinguishes between preM and postM cases. The 20 genes are TCF7L2, C11orf30 (EMSY), ARIH2, MLH1, IRF2BP2, FGFR1OP, NFE2L2, EPC1, SOS1, MLLT4, IL13RA2, GIT2, MAP3K1, SF3B1, ERCC4, ADD3, CHUK, FRK, REEP3 and MAP2K6. The 20 genes were able to distinguish between preM and postM with area under the curve of (AUC) of 0.987 (95% Confidence interval of 0.947 to 1.00) (Figure), sensitivity of 93.8 and specificity of 97.1. Leave-one-out curve showed AUC of 0.893 (95% confidence interval of 0.783 to 1.00). TCF7L2, C11orf30 (EMSY), IRF2BP2, NFE2L2, EPC1 and FRK were highly expressed in preM cases with p values of 0.004, 0.008, 0.007, 0.019, 0.01 and 0.03, respectively. Together this data suggests that breast cancer in patients with no germline predisposition to cancer differ biologically in preM patients as compared to postM tumors and these differences should be considered in treatment and management plans of these patients. Citation Format: Ahmad Charifa, Andre Goy, Andrew Pecora, Deena Graham, Donna McNamara, Andrew Ip, Wanlong Ma, Maher Albitar. The molecular landscape of premenopausal versus postmenopausal breast cancer in patients without inherited predisposition mutations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 929.